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neuroguy123 t1_isjnunn wrote

I think you're overthinking it. Maybe try encoding your data as the vector change from one point to the next if you want to help the network learn about relative changes. See https://arxiv.org/pdf/1308.0850.pdf

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Nyanraltotlapun t1_iso6lqp wrote

For example I encoded it as such. Different features have different scales and I need to normalize it somehow. But because differential encoding produce signet values I have problem with it. I afraid that with normalization I will lost information about direction(sign)

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